1. Field of the Invention
The present invention is directed to a method, system, and article of manufacture for prospect selection using a heuristic statistic when culling or augmenting a prospect list for a given promotion.
2. Description of the Prior Art
Consumer Packaged Goods (CPG) manufacturers pay retail firms to promote their products. Typically, a CPG manufacturer specifies a number of prospects fitting specific criteria to target in a particular promotion to be conducted by a retailer. Using the CPG manufacturer's selection criteria, the retailer queries its customer database (e.g., loyalty card holders) to identify prospective targets. The CPG manufacturer pays the retailer on a per-prospect basis to conduct the promotion. Promotional revenue from sales by the retailer varies according to the number of prospects that the CPG manufacturer targets that the retailer can supply. The process of compiling a list of prospective customers to target in a promotion is known as prospecting.
The problem that the retailer faces in prospecting is that, in general, applying the CPG manufacturer's selection criteria to the retailer's customer database will result in either too many or too few prospects being identified for a given promotion. The retailer is then faced with the problem of either culling prospects in the case of too many prospects, or identifying additional prospects to supplement the initially selected prospect list in the case of too few prospects, in order to meet the desired number of prospects for the promotion. The process of culling or supplementing is manual, laborious and time-consuming, and may not produce the highest-potential list of prospects in terms of expected responsiveness to the promotion.
According to one prior-art solution, after compiling the initial list of prospects through querying its customer database using selection criteria provided by the CPG manufacturer, the retailer determines whether the initial selection has yielded too many or too few prospects for the respective promotion. If too many have been selected, then the list is culled by some ad hoc method, e.g., eliminating those whose customer loyalty card ends in, for instance, 5 or 9. If too few have been selected, then the retailer meets with the CPG manufacturer to try to negotiate a relaxation in the selection criteria, and then determines whether the relaxed criteria generate enough additional prospects to meet the specified number.
If the prospect list must be culled in order to reduce the number of prospects, typical ad hoc methods do not ensure that the highest-potential prospects are retained. As a result, overall response to the promotion may be substantially less than optimal.
If the prospect list must be augmented, and if relaxed selection criteria do not generate a sufficient number of additional prospects, or if the CPG manufacturer decides against relaxing the criteria, then the size of the promotion must be reduced. As a result, the retailer realizes less promotional revenue and reduced sales boost from the promotion. Furthermore, the CPG manufacturer's selection criteria may be based on “best guess” and hence may not identify the highest-potential prospects, again resulting in a less than optimal to the promotion.
It is therefore desirable to provide an improved method, system, and article of manufacture for prospect selection, using a heuristic statistic, when culling or augmenting a prospect list for a given promotion.